Run LLM Without OS
NightRun is an experimental open-source project that addresses this issue by booting a machine directly into a local LLM from a USB drive or microSD card, without loading a conventional OS.By removing the operating system, NightRun makes more RAM and memory bandwidth available for AI inference. The runtime is written in Rust, and during boot it loads a quantized model (1.3 GB to 2.4 GB) directly into RAM while verifying its CRC-32 checksums. It might be easy to think that NightRun is a stripped-down Linux distribution designed to save memory, but that is not the case.
- ▪NightRun is an experimental open-source project that addresses this issue by booting a machine directly into a local LLM from a USB drive or microSD card, without loading a conventional OS.By removing the operating system, NightRun makes mo
- ▪The runtime is written in Rust, and during boot it loads a quantized model (1.3 GB to 2.4 GB) directly into RAM while verifying its CRC-32 checksums.
- ▪It might be easy to think that NightRun is a stripped-down Linux distribution designed to save memory, but that is not the case.
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Record
| Original publisher | CNX Software - Embedded Systems News |
| Canonical URL | https://www.cnx-software.com/2026/07/30/nightrun-uefi-application-boots-a-local-llm-on-raspberry-pi-5-and-x86-pcs-without-an-os/ |
| Publication time | Thu, 30 Jul 2026 16:59:28 +0000 |
| Retrieval time | 2026-07-30T18:57:29.406Z |
| Last seen | 2026-07-30T18:57:29.406Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Posted on July 30, 2026 by Debashis Das - 1 Comment on NightRun UEFI application boots a local LLM on Raspberry Pi 5 and x86 PCs without an OS NightRun UEFI application boots a local LLM on Raspberry Pi 5 and x86 PCs without an OS Running LLMs locally on an SBC or mini PC is a good way to keep your data private, but they typically require a conventional operating system, which uses a good portion of system memory. NightRun is an experimental open-source project that addresses this issue by booting a machine directly into a local LLM from a USB drive or microSD card, without loading a conventional OS.By removing the operating system, NightRun makes more RAM and memory bandwidth available for AI inference.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at CNX Software - Embedded Systems News.
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